Abstract
The extremal coefficient function (ECF) of a max-stable process X on some index set T assigns to each finite subset A T the effective number of independent random variables among the collection {Xt}t∈A. We introduce the class of Tawn-Molchanov processes that is in a 1:1 correspondence with the class of ECFs, thus also proving a complete characterization of the ECF in terms of negative definiteness. The corresponding Tawn-Molchanov process turns out to be exceptional among all max-stable processes sharing the same ECF in that its dependency set is maximal w.r.t. inclusion. This entails sharp lower bounds for the finite dimensional distributions of arbitrary max-stable processes in terms of its ECF. A spectral representation of the Tawn-Molchanov process and stochastic continuity are discussed. We also show how to build new valid ECFs from given ECFs by means of Bernstein functions.
| Original language | English |
|---|---|
| Pages (from-to) | 276-302 |
| Number of pages | 27 |
| Journal | Bernoulli |
| Volume | 21 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Feb 2015 |
Bibliographical note
Publisher Copyright:© 2015 ISI/BS.
Keywords
- Completely alternating
- Dependency set
- Extremal coefficient
- Max-linear model
- Max-stable process
- Negative definite
- Semigroup
- Spectrally discrete
- Tawn-Molchanov process
ASJC Scopus subject areas
- Statistics and Probability
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